Abstract
In rescue missions, time is life, and only when the army arrives the first time around can risk to people’s lives and property be minimized. Therefore, not only does a troop’s transportation require reasonable dispatching but there is also a need to consider the time consumption problem of arriving at the location. Therefore, two factors – the number and time of transportation for disaster relief troops – are especially important. First, this study makes an in-depth analysis of the problem of troop dispatching in rescue and relief work, and proposes a network flow model of deploying troops thereof, thus making it a minimum cost maximum flow problem. Second, it defines the priority path to the existing minimum cost maximum flow algorithm; after joining the priority queue, the improved algorithm is more applicable to the study of a disaster relief troop’s transportation problem. Finally, experiments are done concretely on examples based on real life troop data. The results show that the model can effectively support the disaster relief troop’s transportation problem. The improved algorithm can effectively avoid small capacity and time-consuming deteriorated roads, and its time complexity is lowered from the original \( O(n^{2} ) \) to \( O(n) \) on a path selection judgment. The algorithm results can provide scientific reference for a disposal of contingency plans when danger occurs.
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This work was supported by Shaanxi Provincial Natural Science Foundation of China Youth (2015JQ6224) Colored Nodes and Network Complexity Measure Research.
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Peng, ZS., Gong, QG., Duan, YY., Wang, Y., Gao, ZQ. (2018). Study of a Disaster Relief Troop’s Transportation Problem Based on Minimum Cost Maximum Flow. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data & Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-59463-7_72
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DOI: https://doi.org/10.1007/978-3-319-59463-7_72
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